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Behavior

Behavior. Autonomous Characters. Acknowledgement Much of this material is taken from the work of Craig Reynolds . He maintains a web pages including a rich source of material of steering behavior and the consumate source on flocking . Also see:

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Behavior

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  1. Behavior

  2. Autonomous Characters • Acknowledgement Much of this material is taken from the work of Craig Reynolds. He maintains a web pages including a rich source of material of steering behavior and the consumate source on flocking. Also see: Steering Behaviors For Autonomous Characters by Craig Reynolds

  3. Autonomous Characters • Self-Directed characters "puppets that pull their own strings" -Ann Marion • Situated Live in a world shared by other entities • Embodied Physical manifestation (virtual) • Reactive instinctive, driven by stimulus • Improvisation, life-like behavior

  4. Emergent Behavior • The appearance of consistent global behavior from a set of local rules enforcing independent constraints. • Emergent group behavior is the appearance of coordinated collective behavior of many individuals from individual behaviors based on independent, local interactions.

  5. Emergent Misbehavior? • Permits modular development of complex behaviors • Hard to predict interactions among rules • Sometimes surprising and undesirable behaviors appear in new circumstances or when new rules are added. • Hard to debug.

  6. Three-Tier Hierarchy • Action selection goals and strategies “What to do” • Steering guidance / motion control “How to do it” • Locomotion movement generation “Getting it done”

  7. Cowboy Analogy • Action selection Trail boss: “Fetch that stray.” • Steering Cowboy: “Giddy-up, that away.” • Locomotion Horse “Wilbur!”

  8. Flocks in Film • 1987: Stanley and Stella in: Breaking the Ice, (short) Director: Larry Malone, Producer: Symbolics, Inc. • 1988: Behave, (short) Produced and directed by Rebecca Allen • 1989: The Little Death, (short) Director: Matt Elson, Producer: Symbolics, Inc. • 1992: Batman Returns, (feature) Director: Tim Burton, Producer: Warner Brothers • 1993: Cliffhanger, (feature) Director: Renny Harlin, Producer: Carolco. • 1994: The Lion King, (feature) Director: Allers / Minkoff, Producer: Disney.

  9. Flocks in Film • 1996: From Dusk Till Dawn, (feature) Director: Robert Rodriguez, Producer: Miramax • 1996: The Hunchback of Notre Dame, (feature) Director: Trousdale / Wise, Producer: Disney. • 1997: Hercules, (feature) Director: Clements / Musker, Producer: Disney. • 1997: Spawn, (feature) Director: Dipp₫, Producer: Disney. • 1997: Starship Troopers, (feature) Director: Verhoeven, Producer: Tristar Pictures. • 1998: Mulan, (feature) Director: Bancroft/Cook, Producer: Disney.

  10. Flocks in Film • 1998: Antz, (feature) Director: Darnell/Guterman/Johnson, Producer: DreamWorks/PDI. • 1998: A Bugs Life, (feature) Director: Lasseter/Stanton, Producer: Disney/Pixar. • 1998: The Prince of Egypt, (feature) Director: Chapman/Hickner/Wells, Producer: DreamWorks. • 1999: Star Wars: Episode I--The Phantom Menace, (feature) Director: Lucas, Producer: Lucasfilm. • 2000: Lord of the Rings: the Fellowship of the Ring (feature) Director: Jackson, Producer: New Line Cinema.

  11. Motor Control • Steering Force Integrate to determine acceleration • Thrust – determines speed • Lateral Steering Force – determines direction

  12. Boid Object Representation • Point Mass Vehicle • Mass • Position • Velocity • Orientation • Constrained to align with velocity • Force and Speed Limits (No moment of intertia)

  13. Euler Integration acceleration = steering_force / mass velocity = velocity + acceleration position = position + velocity

  14. Seeking and Fleeing • Aim towards target Desired_velocity = Kp (position – target) Steering = desired_velocity – velocity Seeking and Fleeing Applet (Reynolds)

  15. Pursuing and Avoiding • Target is another moving object • Predict target’s future position • Scale prediction time, T, based on distance to object, Dc T=Dc Pursuing and avoiding applet (Reynolds)

  16. More Behaviors • Evasion Like flee, but predict pursuer’s movement • Arrival Like seek, but step at target Applet (Reynolds) • Obstacle Avoidance • Repulsive force • Aim to boundary • Adjust velocity to be perpendicular to surface normal

  17. Flocking Behaviors • Interactions among members of a group • Local neighborhood

  18. Separation: BoidAvoidance

  19. Alignment

  20. Aggregation

  21. Leader Following • Based on arrival • Target is behind leader • Clear leader’s front • Separation avoids crowding • Applet (Reynolds)

  22. Arbitration of Competing Demands • State Machines • Context dependent selection • Problem: combinatorial explosion • Winner Take All • Choose highest priority goal • Problems: dithering, fairness, and tunnel vision • Blending • Combine output (e.g. sum, average, min, …) • Problem: combination may satisfy no one

  23. Flocking Demos • Flocking Applet (Craig Reynolds) • Fish Schooling (Steve Hughes) • Beach House (Ishihama Yoshiaki ) For more demos see Reynolds “Boids in Java”

  24. Do People Flock? Social psychologist’s report the people tend to travel as singles or in groups of size 2 to 5. “Controlling Steering Behavior for Small Groups of Pedestrians in Virtual Urban Environments” Terry Hostetler, Phd dissertation, 2002

  25. Characteristics of Small Groups • Proximity • Coupled Behavior • Common Purpose • Relationship Between Members

  26. Moving Formations • Pairs: Side by side • Triples: Triangular shape

  27. Stationary Formations Stationary quintuple formed Moving pair approaches stationary triple

  28. Locomotion Model for Walking • Two Parameters • Acceleration • Increase/reduce walking speed • Combination of step length and step rate • Turn • Adjust orientation • Heading direction for forward walking

  29. Action Space Accelerate Accelerate Accelerate Turn Left No Turn Turn Right Coast Coast Coast Turn Left No Turn Turn Right Decelerate Decelerate Decelerate Turn Left No Turn Turn Right

  30. Distributed Preference Voting • Seek best compromise through democratic voting • Delegation of voters: Constraint Proxies • Proxies vote on every possible value of control variable • (Weighed) votes are tallied “Some citizens are more equal than others” (Who said life was fair?) • Winning cell represents best compromise Bias towards incumbents to reduce dithering (Now this is REAL politics)

  31. Vote Tabulation Pursuit Point Tracking Maintain Target Velocity Inertia 1.0 Avoid Peds Maintain Formation Avoid Obstacles 1.0 1.0 Centering 4.0 2.0 5.0 2.0 Electioneer Winning Cell

  32. A Group of Two Following a Path Pursuit Point Tracking Maintain Formation walkway axis -1.0 -1.0 +1.0 -1.0 -1.0 +1.0 -1.0 -1.0 +1.0 +1.0 +1.0 +1.0 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 pursuit point  1.0 2.0 +1.0 +1.0 +3.0 -3.0 -3.0 -1.0 -3.0 -3.0 -3.0 Election for ped 1  ped 2  ped 1 Winning vote = Accelerate/Turn Right

  33. Avoiding an Obstacle -- Trajectory walkway axis walkway axis ped 1 ped 1 ped 2 ped 2 Small look-ahead distance Large look-ahead distance

  34. Interaction Between Pairs -- 1

  35. Interaction Between Pairs -- 2

  36. Interaction Between Pairs -- 3

  37. Motion Control Through Optimization • Space-Time Constraints a great place to start is the Witkin and Kass SIGGRAPH paper Spacetime Constraints Andrew Witkin and Michael Kass, SIGGRAPH, V. 22, N. 4, pp. 159-168, 1988. (See me for class notes)

  38. Legged Motion • Statically Stable Walking • Dynamically Stable Running Legged robots that balance by Marc H. Raibert (1986)    ISBN:0-262-18117-7 Also: Legged Robots by Marc Raibert, CACM, V. 6, N. 29, pp. 499-514 June 1986, (See me for class notes)

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